Abstract
The fully autonomous harvesting of oyster mushrooms in the greenhouse requires the development of a reliable and robust harvesting robot. In this paper, we propose an oyster-mushroom-harvesting robot, which can realize harvesting operations in the entire greenhouse. The two crucial components of the harvesting robot are the perception module and the end-effector. Intel RealSense D435i is adopted to collect RGB images and point cloud images in real time; an improved SSD algorithm is proposed to detect mushrooms, and finally, the existing soft gripper is manipulated to grasp oyster mushrooms. Field experiments exhibit the feasibility and robustness of the proposed robot system, in which the success rate of the mushroom recognition success rate reaches 95%, the harvesting success rate reaches 86.8% (without considering mushroom damage), and the harvesting time for a single mushroom is 8.85 s.
Highlights
The agricultural industry has always been a labor-intensive industry
We developed a greenhouse mushroom-harvesting robot that aims to automate oyster mushroom harvesting instead of humans
Where TP is the number of correctly identified oyster mushrooms, FP is the number of incorrectly identified oyster mushrooms, and FN is the number of missed oyster mushrooms
Summary
The agricultural industry has always been a labor-intensive industry. The reason may be that the crops produced in agriculture usually do not have uniform characteristics, and the agricultural production environment is more complex and diverse than the industrial production environment. Applications and solutions that integrate artificial intelligence and robotics are expected to gradually replace manual work in agricultural production activities. These robots, which require less human intervention, can help farmers manage their crops in the future, and they will be able to address the shortage of food and agricultural labor while significantly increasing productivity. We developed a greenhouse mushroom-harvesting robot that aims to automate oyster mushroom harvesting instead of humans. Considering the specific planting agronomy and greenhouse environment of the mushrooms, we focus on solving the oyster mushroom recognition and harvesting efficiency problem.
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